ENH: Add examples dir: API, main, plot dendrogram

examples/example_api.py

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+from imagecluster import calc as ic
+from imagecluster import postproc as pp
+
+# Create image database in memory. This helps to feed images to the NN model
+# quickly.
+ias = ic.image_arrays('pics/', size=(224,224))
+
+# Create Keras NN model.
+model = ic.get_model()
+
+# Feed images through the model and extract fingerprints (feature vectors).
+fps = ic.fingerprints(ias, model)
+
+# Run clustering on the fingerprints.  Select clusters with similarity index
+# sim=0.5
+clusters = ic.cluster(fps, sim=0.5)
+
+# Create dirs with links to images. Dirs represent the clusters the images
+# belong to.
+pp.make_links(clusters, 'pics/imagecluster/clusters')
+
+# Plot images arranged in clusters.
+pp.visualize(clusters, ias)

examples/example_main.py

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+from imagecluster import main
+
+main.main('pics/', sim=0.65, vis=True, maxelem=30)

examples/plot_dendrogram.py

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+from matplotlib import pyplot as plt
+import numpy as np
+from scipy.cluster.hierarchy import dendrogram
+
+from imagecluster import calc as ic
+
+ias = ic.image_arrays('pics/', size=(224,224))
+model = ic.get_model()
+fps = ic.fingerprints(ias, model)
+clusters,extra = ic.cluster(fps, sim=0.5, extra_out=True)
+
+# linkage matrix Z
+Z = extra['Z']
+
+fig,ax = plt.subplots()
+dendrogram(Z, ax=ax)
+
+# Adjust yaxis labels (values from Z[:,2]) to our definition of the `sim`
+# parameter.
+ymin, ymax = ax.yaxis.get_data_interval()
+tlocs = np.linspace(ymin, ymax, 5)
+ax.yaxis.set_ticks(tlocs)
+tlabels = np.linspace(1, 0, len(tlocs))
+ax.yaxis.set_ticklabels(tlabels)
+ax.set_xlabel("image index")
+ax.set_ylabel("sim")
+
+fig.savefig('dendrogram.png')
+plt.show()